Abstract
The rapid global transition toward sustainable transportation requires the mass deployment of Solar-Powered
Electric Vehicle Charging Infrastructure (SPEVCI). However, the integration of localized photovoltaic arrays, high-capacity
battery storage, and high-voltage charging terminals transforms these installations into highly complex socio-technical
systems. Traditional, deterministic project management methodologies—such as the Critical Path Method (CPM)—rely on
static planning and consistently fail to manage the dynamic supply chain volatility, weather delays, and cross-disciplinary
dependencies inherent to SPEVCI deployment. This paper proposes a novel, hybridized methodology: the Dynamic Lifecycle
and AI-BIM Integration (DLAI) framework. By synthesizing Predictive Agile-AI (PA-AI), AI-Enhanced Systems
Engineering (AESE), and Digital Twin spatial computing, the DLAI framework operates as a continuous, intelligent data
ecosystem. It orchestrates spatial simulation, predictive execution routing, and agile telemetry through an IoT-enabled
centralized feedback loop.